audit-test-coverage

Audit automated test coverage for XML/PDF accounting repositories.

Updated Feb 26, 2026
One-click install
npx skills add https://github.com/ElPoot/contabilidad --skill audit-test-coverage
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: audit-test-coverage
Source: https://github.com/ElPoot/contabilidad/tree/main/.agents/skills/audit-test-coverage
Command: npx skills add https://github.com/ElPoot/contabilidad --skill audit-test-coverage

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill identifies whether the repository relies on manual validation instead of automated tests, helping you uncover gaps that could allow regressions in critical accounting and document-processing logic.

Core Features & Use Cases

  • Tests infrastructure audit: Checks for the presence of test directories and common Python test tooling configurations.
  • Critical-function coverage check: Verifies whether key functions (e.g., classifier, XML parsing, PDF clave extraction) have automated tests.
  • Manual validation documentation review: Looks for TESTING.md or testing guidance inside CLAUDE.md and assesses whether a manual matrix exists.

Quick Start

Ask the AI: "Run audit-test-coverage for the contabilidad repository and report whether automated tests exist, whether critical functions are covered, and what manual validation matrix is documented."

Frequently Asked Questions about audit-test-coverage

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I check if my Python repository has enough test coverage for critical functions?

Checking test coverage involves auditing for test directories, pytest configurations, and CI workflows that validate critical functions. This process reveals whether key operations like XML parsing and PDF extraction are protected against regressions.

What is manual validation risk in CI workflows for accounting document processing?

Manual validation risk arises when accounting document processing relies on manual testing matrices instead of automated pytest suites. This leaves critical XML parsing and PDF extraction functions vulnerable to behavioral regressions during CI workflows.

How do I audit pytest coverage for XML and PDF parsing functions?

Auditing pytest coverage for XML and PDF parsing functions involves searching for test directories, verifying pytest configurations, and checking CI workflows. You then verify whether specific critical functions like classifiers and extraction logic have dedicated automated tests.

Does my repository need automated tests if I already have a manual validation matrix?

Even with a manual validation matrix, a repository needs automated tests because manual processes are frequently skipped or outdated. Automated pytest suites ensure critical accounting document parsing and file-handling functions are consistently protected against regressions.

Can I detect missing automated tests for critical accounting document processing logic?

Detecting missing automated tests for accounting document processing involves auditing for test directories, pytest configurations, and CI workflows. The audit identifies whether critical functions like XML parsing and PDF clave extraction have dedicated test coverage or rely on manual validation.

What are the limitations of relying on manual validation instead of pytest for regression safety?

Limitations of relying on manual validation include inconsistent execution and outdated testing matrices documented in TESTING.md or CLAUDE.md. Without automated CI workflows running pytest, critical accounting document processing functions remain exposed to behavioral regressions.

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